The origin of the X-ray emission from the non-starburst gas-rich luminous infrared galaxies Arp 302
Bibliographic record
Abstract
ABSTRACT We present an analysis of the XMM–Newton observation of luminous infrared merging galaxies Arp 302 and a joint re-analysis of its Chandra observation. In particular, we focus on the more significant X-ray emitter of the pair, Arp 302N. Chandra detects significant soft X-ray emission from the hot gas in the star-forming region of Arp 302N spreading up to 12 kpc. We estimate the star formation rate of Arp 302N to be around 1–2 M⊙ yr−1 based on the X-ray luminosity of the star-forming region, similar to previous measurements at longer wavelengths. Chandra and XMM–Newton observations show evidence of a Si xiii emission line with 86 per cent confidence. Our best-fitting model infers a super-solar silicon abundance in the star-forming region, likely related to the past core-collapse supernovae in this galaxy. Similar silicon overabundance was reported in the circumstellar medium of core-collapse supernova remnants in our Galaxy. We also detect narrow Fe Kα and Fe Kβ (98.6 per cent confidence) emission lines as part of the active galactic nucleus (AGN) emission. Our best-fitting spectral model using mytorus indicates the evidence of a heavily obscured power-law emission with NH > 3 × 1024 cm−2 in addition to a weak, unobscured power-law emission. The scattering fraction of the unobscured power-law emission from Compton-thin materials is 0.7 per cent. All these spectral features suggest evidence of a Seyfert 2-like AGN in Arp 302N. The X-ray measurement of its AGN activity is consistent with the previous Spitzer measurement of the same object.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".